The Company Oneview Healthcare is a global healthcare technology company that empowers hospitals and care providers to deliver better patient experiences through connected digital solutions. This role sits between QA Engineering and Integration Engineering, ensuring complex integrations are tested end-to-end and meet both technical and clinical workflow requirements.
Role Overview The Integration QA Engineer is responsible for ensuring the quality, reliability, and performance of integrations between the Oneview platform and third‑party hospital systems, including Electronic Health Records (EHRs), nutrition management, clinical communications, virtual care, building management systems, IoT and RTLS. This role combines deep QA expertise with strong understanding of system integrations, working across product, engineering, and customer environments to validate end‑to‑end workflows across APIs, integration engines, and user-facing applications. You will act as a quality owner within the customer facing engineering team, ensuring integration scenarios are thoroughly tested, defects are identified early, and releases are delivered with confidence. This includes both hands-on testing and close collaboration with Integration Engineers, Product, and external stakeholders.
Key Responsibilities Integration Quality & Testing
Plan and execute integration testing across third-party systems, including EHRs and partner platforms.
Validate end-to-end workflows across APIs, integration engines, backend services, and UI layers.
Design and execute functional, exploratory, regression, and system tests, including integration scenarios.
Collaborate with customers, partners, and vendors to validate integrations in test and production environments.
Test Design & Execution
Define test scope based on both business functionality and system architecture.
Create and maintain test cases covering business, technical, and edge-case scenarios.
Execute testing across backend services, web, mobile, tablet and hardware platforms.
Contribute to automation strategies to reduce manual regression effort.
Integration Analysis Support
Work with Integration Engineers to understand:
Message flows
Data mappings
Transformations and filters
Validate integrations against defined contracts and workflows.
Ensure correct handling of sensitive data (PII / PHI) within test scenarios.
Defect Management & Troubleshooting
Identify, document, and track defects using Jira and appropriate QA tools.
Diagnose integration and system issues to determine root cause.
Collaborate across Engineering, Product and Integration teams to resolve issues quickly.
Environment & Release Support
Deploy and maintain test environments using CI/CD pipelines (e.g. Octopus).
Support integration validation for releases and customer implementations.
Ensure test coverage and quality gates are met prior to release.
Responsible for manifest creation and management.
Responsible for the validation process of the release handover (by the engineering teams)
Monitoring & Continuous Improvement
Support validation of integration monitoring and alerting.
Identify opportunities to improve:
QA processes
Integration test coverage
Automation and efficiency
Documentation & Collaboration
Document test scenarios, integration behaviours, and known issues.
Contribute to knowledge base and test artefacts.
Participate in Agile ceremonies (planning, refinement, stand-ups, retrospectives).
Work closely with Product, Engineering, Technical Solutions, and external partners.
Work closely with Support engineers to troubleshoot and perform RCA for customer incidents
Work with support and customer facing engineers to process and document SOPs
Skills & Experience Experience
5+ years' experience in QA, Test Engineering, or Integration Testing.
Experience working in Agile product environments.
Experience testing integrations across APIs or integration platforms.
Technical Skills Understanding of:
APIs (REST/SOAP)
Integration engines (e.g. Mirth Connect preferred)
Healthcare standards (HL7, FHIR) desirable
Experience with:
Test management tools (e.g. TestRail)
Defect tracking tools (e.g. Jira)
CI/CD pipelines and deployment tooling
Database knowledge (SQL) essential
Exposure to cloud platforms (AWS/Azure) required
Experience with AI tools:
Prompt engineering for test automation
LLM-Powered Test Infrastructure
Risk and Privacy Management over AI tools
Evaluating and Refining AI outputs Strategic AI Adoption